FEMA National Risk Index
Data for Charlottesville Region
Michele Claibourn
6/24/2021
Data Source
Source: FEMA, National Risk Index, October 2020 release.
Variable descriptions
glimpse(nri)## Rows: 50
## Columns: 76
## $ OID_ <dbl> 47346, 47471, 48413, 48503, 48508, 48509, 48904, 48905, 489…
## $ NRI_ID <chr> "T51065020101", "T51065020300", "T51003010201", "T510790301…
## $ STATE <chr> "Virginia", "Virginia", "Virginia", "Virginia", "Virginia",…
## $ STATEABBRV <chr> "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA", "VA",…
## $ STATEFIPS <dbl> 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51, 51,…
## $ COUNTY <chr> "Fluvanna", "Fluvanna", "Albemarle", "Greene", "Albemarle",…
## $ COUNTYTYPE <chr> "County", "County", "County", "County", "County", "County",…
## $ COUNTYFIPS <chr> "065", "065", "003", "079", "003", "003", "003", "003", "07…
## $ STCOFIPS <dbl> 51065, 51065, 51003, 51079, 51003, 51003, 51003, 51003, 510…
## $ TRACT <chr> "020101", "020300", "010201", "030102", "010800", "011000",…
## $ TRACTFIPS <dbl> 51065020101, 51065020300, 51003010201, 51079030102, 5100301…
## $ POPULATION <dbl> 5571, 5311, 4664, 5393, 5325, 6292, 3765, 3738, 9145, 9341,…
## $ BUILDVALUE <dbl> 551401000, 530703000, 589443000, 569304000, 707799000, 1265…
## $ AGRIVALUE <dbl> 1000124.0179, 2454071.5733, 998608.4291, 2592134.2808, 1253…
## $ AREA <dbl> 43.2172270, 101.6045726, 27.0136979, 63.8718600, 5.3042504,…
## $ CFLD_EVNTS <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_AFREQ <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPPE <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_EXPT <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_HLRB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_HLRP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ CFLD_HLRR <chr> "Not Applicable", "Not Applicable", "Not Applicable", "Not …
## $ DRGT_EVNTS <dbl> 126, 154, 70, 70, 77, 77, 91, 91, 63, 105, 154, 70, 98, 126…
## $ DRGT_AFREQ <dbl> 7.000000, 8.555556, 3.888889, 3.888889, 4.277778, 4.277778,…
## $ DRGT_EXPB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_EXPP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_EXPPE <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_EXPA <dbl> 611186.8998, 2096304.6178, 898747.5862, 2592134.2808, 12536…
## $ DRGT_EXPT <dbl> 611186.8998, 2096304.6178, 898747.5862, 2592134.2808, 12536…
## $ DRGT_HLRB <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_HLRP <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,…
## $ DRGT_HLRA <dbl> 0.003197017, 0.003197017, 0.003222722, 0.004763245, 0.00322…
## $ DRGT_HLRR <chr> "Very High", "Very High", "Very High", "Very High", "Very H…
## $ HWAV_EVNTS <dbl> 8, 8, 6, 6, 6, 6, 6, 6, 12, 8, 5, 6, 6, 8, 5, 12, 6, 6, 6, …
## $ HWAV_AFREQ <dbl> 0.6589786, 0.6589786, 0.4942339, 0.3947789, 0.4942339, 0.49…
## $ HWAV_EXPB <dbl> 551400513, 530702957, 589442851, 546678926, 707799000, 1265…
## $ HWAV_EXPP <dbl> 5570.997, 5311.000, 4663.998, 5231.000, 5325.000, 6291.996,…
## $ HWAV_EXPPE <dbl> 41225376461, 39301398589, 34513586247, 38709396581, 3940500…
## $ HWAV_EXPT <dbl> 41776776974, 39832101546, 35103029097, 39256075507, 4011279…
## $ HWAV_HLRB <dbl> 1.169e-12, 1.169e-12, 1.169e-12, 1.169e-12, 1.169e-12, 1.16…
## $ HWAV_HLRP <dbl> 3.971792e-07, 3.971792e-07, 1.058701e-07, 5.350162e-07, 1.0…
## $ HWAV_HLRR <chr> "Very Low", "Very Low", "Very Low", "Relatively Low", "Very…
## $ HRCN_EVNTS <dbl> 6, 7, 9, 9, 9, 9, 9, 9, 9, 6, 8, 9, 9, 5, 8, 9, 8, 8, 8, 4,…
## $ HRCN_AFREQ <dbl> 0.06582491, 0.06589680, 0.07046340, 0.07180899, 0.06582491,…
## $ HRCN_EXPB <dbl> 550733910, 530380270, 589442851, 569303923, 704074505, 1265…
## $ HRCN_EXPP <dbl> 5564.073, 5307.788, 4663.998, 5393.000, 5312.928, 6291.648,…
## $ HRCN_EXPPE <dbl> 41174136929, 39277633809, 34513586247, 39908196307, 3931566…
## $ HRCN_EXPT <dbl> 41724870839, 39808014079, 35103029097, 40477500230, 4001973…
## $ HRCN_HLRB <dbl> 0.0001627591, 0.0001627591, 0.0001627591, 0.0001627591, 0.0…
## $ HRCN_HLRP <dbl> 1.432476e-06, 1.432476e-06, 1.432476e-06, 1.599039e-06, 1.4…
## $ HRCN_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ RFLD_EVNTS <dbl> 3, 3, 59, 37, 59, 59, 59, 59, 37, 3, 44, 59, 59, 7, 44, 59,…
## $ RFLD_AFREQ <dbl> 0.1363636, 0.1363636, 2.6818182, 1.6818182, 2.6818182, 2.68…
## $ RFLD_EXPB <dbl> 1649205.9, 3600534.0, 14450941.1, 3620317.5, 699096.0, 2420…
## $ RFLD_EXPP <dbl> 11.836098, 35.576304, 102.666978, 36.554255, 5.629246, 120.…
## $ RFLD_EXPPE <dbl> 87587125, 263264651, 759735634, 270501484, 41656421, 893340…
## $ RFLD_EXPA <dbl> 50281.8794, 168074.2006, 44928.6765, 85771.0354, 488.6131, …
## $ RFLD_EXPT <dbl> 89286613, 267033259, 774231504, 274207572, 42356006, 917627…
## $ RFLD_HLRB <dbl> 2.251579e-04, 2.251579e-04, 4.212615e-05, 2.905738e-03, 4.2…
## $ RFLD_HLRP <dbl> 4.003475e-05, 4.003475e-05, 9.587986e-06, 4.040050e-06, 9.5…
## $ RFLD_HLRA <dbl> 0.009312590, 0.009312590, 0.011180959, 0.009741927, 0.01118…
## $ RFLD_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ SWND_EVNTS <dbl> 369, 368, 390, 396, 368, 369, 369, 368, 397, 369, 363, 369,…
## $ SWND_AFREQ <dbl> 11.53125, 11.52825, 12.20950, 12.40625, 11.53125, 11.53125,…
## $ SWND_EXPB <dbl> 551401000, 530703000, 589443000, 569304000, 707799000, 1265…
## $ SWND_EXPP <dbl> 5571, 5311, 4664, 5393, 5325, 6292, 3765, 3738, 9145, 9341,…
## $ SWND_EXPPE <dbl> 41225400000, 39301400000, 34513600000, 39908200000, 3940500…
## $ SWND_EXPA <dbl> 1000124.0179, 2454071.5733, 998608.4291, 2592134.2808, 1253…
## $ SWND_EXPT <dbl> 41777801124, 39834557072, 35104041608, 40480096134, 4011292…
## $ SWND_HLRB <dbl> 8.246272e-06, 8.246272e-06, 2.383243e-06, 7.876500e-06, 2.3…
## $ SWND_HLRP <dbl> 2.889675e-07, 2.889675e-07, 3.395608e-07, 2.939429e-07, 3.3…
## $ SWND_HLRA <dbl> 0.0001960432, 0.0001960432, 0.0003132078, 0.0002843516, 0.0…
## $ SWND_HLRR <chr> "Very Low", "Very Low", "Very Low", "Very Low", "Very Low",…
## $ NRI_VER <chr> "October 2020", "October 2020", "October 2020", "October 20…Observations are census tract estimates of…
- Population, building value, agricultural value within tract, area of tract
- Natural hazards include: CFLD - coastal flooding, DRGT - drought, HWAV - heat wave, HRCN - hurricane, RFLD - riverine flooding, SWND - strong wind
- Hazard measures include: EVNTS - number of events in recording period, AFREQ - annualized frequency (# events/# years in recording period)
- Exposure measures include: EXPB - building value exposure, EXPP - population exposure, EXPE - population equivalence exposure, EXPA - agricultural value exposure
- Historic loss ratio measures include: HLRB - historic loss ratio for building value, HLRA - historicla loss ratio for agriculture, HLRP - historical loss ratio for population, HLRR - historic loss ratio overall
Summaries
5-number summaries of (non-missing) numeric variables (remove tract identifiers)
nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>%
select(where(~is.numeric(.x) && !is.na(.x))) %>%
as.data.frame() %>%
stargazer(., type = "text", title = "Summary Statistics", digits = 0,
summary.stat = c("mean", "sd", "min", "median", "max"))##
## Summary Statistics
## =====================================================================================
## Statistic Mean St. Dev. Min Median Max
## -------------------------------------------------------------------------------------
## POPULATION 4,694 1,741 1,900 4,382 9,341
## BUILDVALUE 600,914,960 274,394,213 210,947,000 559,413,000 1,352,245,000
## AGRIVALUE 1,701,520 2,542,400 0 931,421 13,226,654
## AREA 43 53 0 18 195
## DRGT_EVNTS 97 24 63 91 161
## DRGT_AFREQ 5 1 4 5.1 9
## DRGT_EXPA 1,372,734 2,012,315 0 596,796 8,841,211
## DRGT_EXPT 1,372,734 2,012,315 0 596,796 8,841,211
## DRGT_HLRA 0 0 0 0 0
## HWAV_EVNTS 7 2 5 6 12
## HWAV_AFREQ 1 0 0 0 1
## HWAV_EXPB 594,263,002 268,213,179 210,947,000 549,039,719 1,352,244,990
## HWAV_EXPP 4,678 1,740 1,900 4,351 9,341
## HWAV_EXPPE 34,615,220,205 12,878,768,794 14,060,000,000 32,197,399,778 69,123,399,489
## HWAV_EXPT 35,209,483,206 13,089,228,055 14,270,947,000 32,668,421,302 70,475,644,479
## HWAV_HLRB 0 0 0 0 0
## HWAV_HLRP 0 0 0 0 0
## HRCN_EVNTS 8 1 4 9 9
## HRCN_AFREQ 0 0 0 0 0
## HRCN_EXPB 599,680,668 274,451,546 210,947,000 559,079,443 1,349,737,674
## HRCN_EXPP 4,689 1,744 1,900 4,382 9,321
## HRCN_EXPPE 34,695,606,309 12,903,118,962 14,060,000,000 32,426,797,882 68,974,004,894
## HRCN_EXPT 35,295,286,977 13,115,107,535 14,270,947,000 32,941,525,397 70,323,742,568
## HRCN_HLRB 0 0 0 0 0
## HRCN_HLRP 0 0 0 0 0
## RFLD_EVNTS 30 25 0 15 59
## RFLD_AFREQ 1 1 0 1 3
## RFLD_EXPB 13,388,752 13,835,303 0 8,427,838 54,305,747
## RFLD_EXPP 89 93 0 62 416
## RFLD_EXPPE 661,263,174 690,685,745 0 460,988,960 3,081,542,905
## RFLD_EXPA 153,755 313,700 0 38,504 1,708,403
## RFLD_EXPT 674,805,682 703,954,174 0 469,495,154 3,137,557,055
## RFLD_HLRB 0 0 0 0 0
## RFLD_HLRP 0 0 0 0 0
## RFLD_HLRA 0 0 0 0 0
## SWND_EVNTS 369 9 354 368 397
## SWND_AFREQ 12 0 11 12 12
## SWND_EXPB 600,914,960 274,394,213 210,947,000 559,413,000 1,352,245,000
## SWND_EXPP 4,694 1,741 1,900 4,382 9,341
## SWND_EXPPE 34,737,376,000 12,882,414,388 14,060,000,000 32,426,800,000 69,123,400,000
## SWND_EXPA 1,701,520 2,542,400 0 931,421 13,226,654
## SWND_EXPT 35,339,992,480 13,094,503,181 14,270,950,433 32,954,976,874 70,475,710,779
## SWND_HLRB 0 0 0 0 0
## SWND_HLRP 0 0 0 0 0
## SWND_HLRA 0 0 0 0 0
## -------------------------------------------------------------------------------------Summaries of (non-missing) character variables (remove tract identifiers)
nri %>% select(-c(OID_:STATEFIPS, COUNTYTYPE:TRACTFIPS, NRI_VER)) %>%
select(where (~is.character(.x))) %>% map(tabyl)## $COUNTY
## .x[[i]] n percent
## Albemarle 22 0.44
## Charlottesville 12 0.24
## Fluvanna 4 0.08
## Greene 3 0.06
## Louisa 6 0.12
## Nelson 3 0.06
##
## $CFLD_HLRR
## .x[[i]] n percent
## Not Applicable 50 1
##
## $DRGT_HLRR
## .x[[i]] n percent
## No Rating 12 0.24
## Relatively Moderate 9 0.18
## Very High 29 0.58
##
## $HWAV_HLRR
## .x[[i]] n percent
## Relatively Low 3 0.06
## Very Low 47 0.94
##
## $HRCN_HLRR
## .x[[i]] n percent
## Very Low 50 1
##
## $RFLD_HLRR
## .x[[i]] n percent
## No Rating 8 0.16
## Very Low 42 0.84
##
## $SWND_HLRR
## .x[[i]] n percent
## Very Low 50 1Visual distribution
Via a grouped series of histograms
Tract assets
nri %>% select(TRACTFIPS:AREA) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
geom_histogram() +
facet_wrap(~measure, scales = "free")
Tract hazards: Drought
nri %>% select(contains("DRGT"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Heat Wave
nri %>% select(contains("HWAV"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Hurricane
nri %>% select(contains("HRCN"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Riverine Flooding
nri %>% select(contains("RFLD"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Tract hazards: Strong Wind
nri %>% select(contains("SWND"), TRACTFIPS) %>% select(-contains("HLRR")) %>%
pivot_longer(-TRACTFIPS, names_to = "measure", values_to = "value") %>%
ggplot(aes(x = value, fill = measure)) +
geom_histogram() +
scale_fill_viridis(option = "plasma", discrete = TRUE, guide = FALSE) +
facet_wrap(~measure, scales = "free")
Maps
Droughts
# DRGT
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$DRGT_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = cville_nri,
fillColor = ~pal(DRGT_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
"Ann. Freq.: ", round(cville_nri$DRGT_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = cville_nri$DRGT_AFREQ,
title = "Drought-#/year", opacity = 0.7)Heat Wave
# HWAV
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$HWAV_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = cville_nri,
fillColor = ~pal(HWAV_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
"Ann. Freq.: ", round(cville_nri$HWAV_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = cville_nri$HWAV_AFREQ,
title = "Heat Wave-#/year", opacity = 0.7)Hurricane
# HRCN
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$HRCN_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = cville_nri,
fillColor = ~pal(HRCN_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
"Ann. Freq.: ", round(cville_nri$HRCN_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = cville_nri$HRCN_AFREQ,
title = "Hurricane-#/year", opacity = 0.7)Riverine Flooding
# RFLD
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$RFLD_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = cville_nri,
fillColor = ~pal(RFLD_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
"Ann. Freq.: ", round(cville_nri$RFLD_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = cville_nri$RFLD_AFREQ,
title = "Riverine Flooding-#/year", opacity = 0.7)Strong Wind
# SWND
pal <- colorNumeric("plasma", reverse = TRUE, domain = cville_nri$SWND_AFREQ) # viridis
leaflet() %>%
addProviderTiles("CartoDB.Positron") %>%
addPolygons(data = cville_nri,
fillColor = ~pal(SWND_AFREQ),
weight = 1,
opacity = 1,
color = "white",
fillOpacity = 0.6,
highlight = highlightOptions(
weight = 2,
fillOpacity = 0.8,
bringToFront = T
),
popup = paste0("Tract Number: ", cville_nri$NAME, "<br>",
"Ann. Freq.: ", round(cville_nri$SWND_AFREQ, 2))
) %>%
addLegend("bottomright", pal = pal, values = cville_nri$SWND_AFREQ,
title = "Strong Wind-#/year", opacity = 0.7)Nota Bene
- Coastal flooding not relevant for this region.
- Most hazard overall ratings are very low or no ratings, except for drought; relative to larger national variation, these do not represent high risks.
- Several hazard rates are dominated by regional effects, with little variation within th region.